Method and system for minimizing time-variant energy demand and consumption of built environment

ABSTRACT

A computer-implemented method and system is provided. The system manipulates load curves corresponding to time-variant energy demand and consumption of a built environment. The system analyzes a first, second, third, fourth and a fifth set of data. The first set of data is associated with energy consuming devices. The second set of data is associated with an occupancy behavior of users. The third set of data is associated with energy storage and supply means. The fourth set of data is associated with environmental sensors. The fifth set of data is associated with energy pricing models. The system executes control routines for controlling peak loading conditions associated with the built environment. The system manipulates an optimized operating state of the energy consuming devices. The system integrates the energy storage and supply means for optimal reduction of the peak level of energy demand concentrated over the limited period of time.

CROSS-REFERENCES TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.15/590,104, filed on May 9, 2017, entitled “METHOD AND SYSTEM FORMINIMIZING TIME-VARIANT ENERGY DEMAND AND CONSUMPTION OF BUILTENVIRONMENT,” which claims the benefit under 35 U.S.C. § 119(e) of thefiling date of U.S. Provisional Patent Application No. 62/334,367, filedon May 10, 2016, entitled “METHOD AND SYSTEM FOR REDUCING THE ENERGYDEMAND OF A BUILDING OR GRID NETWORK.” The disclosures of the aboveapplications are incorporated by reference in their entireties as a partof this document.

TECHNICAL FIELD

The present disclosure relates to a field of energy management system.More specifically, the present disclosure relates to a method and systemfor manipulating load curves corresponding to time-variant energy demandand consumption of a built environment associated with one or morerenewable energy sources.

BACKGROUND

Over the last few decades, increasing population and energy requirementsto power modern transportation and electronic technologies result in arapid development in energy generation and distribution technology. Inorder to meet the energy generation and distribution requirements,energy utilities depend mostly on the non-renewable energy sources likefossil fuels which produce a high amount of carbon emissions. Refinementprocesses of fossil fuels and/or its by-products and their combustion todrive electric generators have contributed as one of the major cause ofexcessive carbon emissions. The release of carbon and other chemicalby-products into the atmosphere has impacted temperatures and climatepatterns on a global scale. The increased awareness of the impacts ofcarbon emissions from the use of fossil fueled electric generation alongwith the increased cost of producing high power during peak loadconditions has increased the need for alternative solutions. Thesealternative solutions are referred to as renewable energy sources, whichmay be used to generate electricity. These renewable energy sources maybe applied to electric drive trains, electric automation andtransportation, without the need to extract, transport, refine, combust,and release carbon-based fossil fuels. Renewable energy comes in manyforms, but significantly is generated by capturing energy from natural,non-carbon intensive sources such as wind, sunlight, water movement,geothermal and other new sources as they are discovered and improved.Unlike fossil fuels and/or its by-products, these renewable energysources are complex in nature as they are intermittent and cannot becontrolled actively by humans. This enhances the probability ofoccurrence of certain time periods where power production far exceedsdemands or certain time periods where power production falls short ofdemands. This creates major challenges for energy utilities to makeinvestments, generate power for sale and profit. Also, this createsmajor challenges for the markets in establishing a price of energy forconsumers. Nowadays, energy storage means are deployed to store energywhen power production is excessive and release energy when demandsexceed power production output. These energy storage means include butmay not be limited to batteries and sophisticated power banks. However,there are many limitations to the effective installation of the energystorage means due to sizing requirements, specific load profiles andother attributes which must be matched very carefully in order toprovide feasible economic returns.

SUMMARY

In a first example, a computer-implemented method is provided. Thecomputer-implemented method for manipulation of load curvescorresponding to time-variant energy demand and consumption of a builtenvironment associated with one or more renewable energy sources. Thecomputer-implemented method may include a first step of analysis of afirst set of statistical data, a second set of statistical data, a thirdset of statistical data, a fourth set of statistical data and a fifthset of statistical data. The first set of statistical data is associatedwith a plurality of energy consuming devices. The second set ofstatistical data is associated with an occupancy behavior of a pluralityof users. The third set of statistical data is associated with aplurality of energy storage and supply means. The fourth set ofstatistical data is associated with a plurality of environmental sensorsand a fifth set of statistical data is associated with a plurality ofenergy pricing models. The computer-implemented method may include asecond step of execution of one or more control routines for controllingpeak loading conditions associated with the built environment. Thecomputer-implemented method may include a third step of manipulation ofan optimized operating state of each of the plurality of energyconsuming devices. The computer-implemented method may include a fourthstep of integration of the plurality of energy storage and supply meansfor providing an equivalent real time energy supply to selected energyconsuming devices of the plurality of energy consuming devices. Theanalysis may be done by performing one or more statistical functions togenerate a plurality of statistical results. The execution may beperformed based on the plurality of statistical results. The one or morecontrol routines may be executed by performing at least one of aplurality of control techniques. The plurality of control techniques maybe performed for generation of an optimized time variant energy demandand consumption and rendering one or more gradual load curves associatedwith the built environment. The operating state of the plurality ofenergy consuming devices may be manipulated by time-variant shifting ofenergy usage of each selected energy consuming device of the pluralityof energy consuming devices in a scheduled energy usage profile of theselected energy consuming device of the plurality of energy consumingdevices. The time-variant shifting and scheduling may be performed forgeneration of a peak level of energy demand concentrated over a limitedperiod of time and rendering one or more steep load curves associatedwith the built environment. The integration may be performed based onvalidation of an increase in the energy demand above a threshold level.The integration may be performed for optimally reducing the peak levelof energy demand concentrated over the limited period of time. Theoptimal reduction of the peak level of energy demand provides at leastone of a first potential for optimum charge and a second potential ofoptimum discharge of the plurality of energy storage and supply meansover a period of time.

In a second example, a computer system is provided. The computer systemmay include one or more processors and a memory coupled to the one ormore processors. The memory may store instructions which, when executedby the one or more processors, may cause the one or more processors toperform a method. The method manipulates load curves corresponding totime-variant energy demand and consumption of a built environmentassociated with one or more renewable energy sources. The method mayinclude a first step of analysis of a first set of statistical data, asecond set of statistical data, a third set of statistical data, afourth set of statistical data and a fifth set of statistical data. Thefirst set of statistical data is associated with a plurality of energyconsuming devices. The second set of statistical data is associated withan occupancy behavior of a plurality of users. The third set ofstatistical data is associated with a plurality of energy storage andsupply means. The fourth set of statistical data is associated with aplurality of environmental sensors and a fifth set of statistical datais associated with a plurality of energy pricing models. The method mayinclude a second step of execution of one or more control routines forcontrolling peak loading conditions associated with the builtenvironment. The method may include a third step of manipulation of anoptimized operating state of each of the plurality of energy consumingdevices. The method may include a fourth step of integration of theplurality of energy storage and supply means for providing an equivalentreal time energy supply to selected energy consuming devices of theplurality of energy consuming devices. The analysis may be done byperforming one or more statistical functions to generate a plurality ofstatistical results. The execution may be performed based on theplurality of statistical results. The one or more control routines maybe executed by performing at least one of a plurality of controltechniques. The plurality of control techniques may be performed forgeneration of an optimized time variant energy demand and consumptionand rendering one or more gradual load curves associated with the builtenvironment. The operating state of the plurality of energy consumingdevices may be manipulated by time-variant shifting of energy usage ofeach selected energy consuming device of the plurality of energyconsuming devices in a scheduled energy usage profile of the selectedenergy consuming device of the plurality of energy consuming devices.The time-variant shifting and scheduling may be performed for generationof a peak level of energy demand concentrated over a limited period oftime and rendering one or more steep load curves associated with thebuilt environment. The integration may be performed based on validationof an increase in the energy demand above a threshold level. Theintegration may be performed for optimally reducing the peak level ofenergy demand concentrated over the limited period of time. The optimalreduction of the peak level of energy demand provides at least one of afirst potential for optimum charge and a second potential of optimumdischarge of the plurality of energy storage and supply means over aperiod of time.

In a third example, a computer-readable storage medium is provided. Thecomputer-readable storage medium encodes computer executableinstructions that, when executed by at least one processor, performs amethod. The method manipulates load curves corresponding to time-variantenergy demand and consumption of a built environment associated with oneor more renewable energy sources. The method may include a first step ofanalysis of a first set of statistical data, a second set of statisticaldata, a third set of statistical data, a fourth set of statistical dataand a fifth set of statistical data. The first set of statistical datais associated with a plurality of energy consuming devices. The secondset of statistical data is associated with an occupancy behavior of aplurality of users. The third set of statistical data is associated witha plurality of energy storage and supply means. The fourth set ofstatistical data is associated with a plurality of environmental sensorsand a fifth set of statistical data is associated with a plurality ofenergy pricing models. The method may include a second step of executionof one or more control routines for controlling peak loading conditionsassociated with the built environment. The method may include a thirdstep of manipulation of an optimized operating state of each of theplurality of energy consuming devices. The method may include a fourthstep of integration of the plurality of energy storage and supply meansfor providing an equivalent real time energy supply to selected energyconsuming devices of the plurality of energy consuming devices. Theanalysis may be done by performing one or more statistical functions togenerate a plurality of statistical results. The execution may beperformed based on the plurality of statistical results. The one or morecontrol routines may be executed by performing at least one of aplurality of control techniques. The plurality of control techniques maybe performed for generation of an optimized time variant energy demandand consumption and rendering one or more gradual load curves associatedwith the built environment. The operating state of the plurality ofenergy consuming devices may be manipulated by time-variant shifting ofenergy usage of each selected energy consuming device of the pluralityof energy consuming devices in a scheduled energy usage profile of theselected energy consuming device of the plurality of energy consumingdevices. The time-variant shifting and scheduling may be performed forgeneration of a peak level of energy demand concentrated over a limitedperiod of time and rendering one or more steep load curves associatedwith the built environment. The integration may be performed based onvalidation of an increase in the energy demand above a threshold level.The integration may be performed for optimally reducing the peak levelof energy demand concentrated over the limited period of time. Theoptimal reduction of the peak level of energy demand provides at leastone of a first potential for optimum charge and a second potential ofoptimum discharge of the plurality of energy storage and supply meansover a period of time.

BRIEF DESCRIPTION OF THE FIGURES

Having thus described the invention in general terms, reference will nowbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 illustrates an interactive environment for manipulating loadcurves corresponding to time-variant energy demand and consumption of abuilt environment, in accordance with various embodiments of the presentdisclosure;

FIG. 2 illustrates a block diagram for manipulating the load curvescorresponding to the time-variant energy demand and consumption of thebuilt environment, in accordance with various embodiments of the presentdisclosure;

FIG. 3 illustrates a block diagram of an energy demand control system,in accordance with various embodiments of the present disclosure;

FIG. 4 illustrates a flow chart for manipulating the load curves, inaccordance with various embodiments of the present disclosure; and

FIG. 5 illustrates a block diagram of a communication device, inaccordance with various embodiments of the present disclosure.

It should be noted that the accompanying figures are intended to presentillustrations of exemplary embodiments of the present disclosure. Thesefigures are not intended to limit the scope of the present disclosure.It should also be noted that accompanying figures are not necessarilydrawn to scale.

DETAILED DESCRIPTION

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present technology. It will be apparent, however,to one skilled in the art that the present technology can be practicedwithout these specific details. In other instances, structures anddevices are shown in block diagram form only in order to avoid obscuringthe present technology.

Reference in this specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the present technology. The appearance of the phrase “in oneembodiment” in various places in the specification are not necessarilyall referring to the same embodiment, nor are separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by some embodiments andnot by others. Similarly, various requirements are described which maybe requirements for some embodiments but not other embodiments.

Moreover, although the following description contains many specifics forthe purposes of illustration, anyone skilled in the art will appreciatethat many variations and/or alterations to said details are within thescope of the present technology. Similarly, although many of thefeatures of the present technology are described in terms of each other,or in conjunction with each other, one skilled in the art willappreciate that many of these features can be provided independently ofother features. Accordingly, this description of the present technologyis set forth without any loss of generality to, and without imposinglimitations upon, the present technology.

FIG. 1 illustrates an interactive environment for manipulating loadcurves corresponding to time-variant energy demand and consumption of abuilt environment, in accordance with various embodiment of the presentdisclosure. The interactive environment facilitates assimilation andanalysis of energy conditions associated with the one or more builtenvironments. The energy conditions include but may not be limited toenergy demand, energy consumption, energy expenses and energy useintensity. The energy conditions are utilized for execution of one ormore control routines to control peak loading conditions and abruptchanges in energy pricing associated with the one or more builtenvironments. In addition, the energy conditions are utilized formanipulation of load curves to efficiently reduce the time-variantenergy demand and consumption of the one or more built environments.

The interactive environment is characterized by the interaction of abuilt environment 102, a plurality of energy consuming devices 104, aplurality of energy storage and supply means 106, a plurality of sensors108 and one or more data collecting devices 110. In addition, theinteractive environment is characterized by the interaction of acommercial power supply grid node 112, one or more renewable energysupply sources 114 and a communication network 116. Furthermore, theinteractive environment is characterized by the interaction of aplurality of environmental sensors 118 and a plurality of energy pricingmodels 120. Moreover, the interactive environment is characterized bythe interaction of a energy demand control system 122, a plurality ofexternal application program interfaces 124 (hereafter “APIs”) and oneor more statistical monitoring devices 126.

In general, the built environment 102 is a closed or semi-closedstructure with one or more number of floors utilized for specificpurposes. Each built environment are utilized to perform a pre-definedoperations and maintenance based on types of services provided by thebuilt environment 102. The types of services include hospitality,travel, work, entertainment, manufacturing and the like. In addition,each type of service provided decides a scale of the operations andmaintenance of the built environment 102. The type of services and themaintenance pertains to the energy consumption associated with each ofthe plurality of energy consuming devices 104. Examples of the builtenvironment 102 includes but may not be limited to an office, a mall, anairport, a stadium, a hotel and a manufacturing plant.

The built environment 102 utilizes energy for operations and maintenanceof the built environment 102. The built environment 102 obtains theenergy from a plurality of energy generation and supply sources. Theplurality of energy generation and supply sources include but may not belimited to the commercial power supply grid node 112 and the one or morerenewable energy supply sources 114. The commercial power supply gridnode 112 corresponds to a network of power lines, a plurality oftransformers and one or more equipment employed for the transmission anddistribution of the alternate current power to the built environment102. Further, the one or more renewable energy supply sources 114include but may not be limited to one or more windmills and a pluralitysolar photovoltaic panels.

In an embodiment of the present disclosure, the one or more renewableenergy supply sources 114 are deployed at the built environment 102. Inan example, the plurality of solar photovoltaic panels are installed atthe residential or commercial rooftops. In another embodiment of thepresent disclosure, the one or more renewable energy supply sources 114are deployed at a remote location from the built environment 102. In anexample, the one or more windmills are deployed at countryside farmland.In an embodiment of the present disclosure, the one or more renewableenergy supply sources 114 is directly connected to the plurality ofenergy storage and supply means 106 associated with the builtenvironment 102. The one or more renewable energy supply sources 114directly provides DC energy to the plurality of energy storage andsupply means 106 without going through any voltage or current conversionprocess. In another embodiment of the present disclosure, the one ormore renewable energy supply sources 114 is connected with the builtenvironment 102 to supply available energy through the use of a directcurrent to alternating current inverter.

The plurality of energy storage and supply means 106 is configured tostore the energy and supply to fulfil energy demand associated with thebuilt environment 102. In an embodiment of the present disclosure, theplurality of energy storage and supply means 106 includes one or morebattery cells assembled to create one or more battery packs capable ofcharging and discharging electric energy. In another embodiment of thepresent disclosure, the plurality of energy storage and supply means 106is a high speed flywheel energy storage means. In yet another embodimentof the present disclosure, the plurality of energy storage and supplymeans 106 is pumped hydro energy storage means.

In yet another embodiment of the present disclosure, the plurality ofenergy storage and supply means 106 is non-electrical energy storingmediums. In an example, the energy storage and supply means may becomprised of thermal mass or momentum, such that the calculated amountof energy as converted to heat is stored within the energy storage andsupply means. In addition, the energy is stored and released at acertain rate using heat transfer or pumping as an energy transfermedium. In another example, a building environment, its construction,envelope and contents are utilized as a means to store, transfer andrelease energy passively or actively in a form of heat when combinedwith a means of artificial heating and cooling.

In an embodiment of the present disclosure, the plurality of energystorage and supply means 106 is located at a central location in thebuilt environment 102. The central location associated with the builtenvironment 102 include an electrical room or closet, exterior in aspecialized storage cabinet or container and the like. In anotherembodiment of the present disclosure, the plurality of energy storageand supply means 106 is co-located with each of the plurality of energyconsuming devices 104. In yet another embodiment of the presentdisclosure, the plurality of energy storage and supply means 106 isdistributed throughout the built environment 102. In an example, theplurality of energy storage and supply means 106 is distributed instand-alone forms, plug-in forms and design oriented forms such asfurniture or permanent wall hanging forms or picture frames.

In yet another embodiment of the present disclosure, the plurality ofenergy storage and supply means 106 is built into the building structureor building electrical distribution itself. In yet another embodiment ofthe present disclosure, the plurality of energy storage and supply means106 is in a form of thermal heat mass capture and release usingcalculated capacities of building materials. In yet another embodimentof the present disclosure, the plurality of energy storage and supplymeans is located outside of the built environment 102 in a micro-grid orfractal grid application.

Going further, the built environment 102 is associated with a pluralityof users 128 present inside the built environment 102. The plurality ofusers 128 may be any human operator, human worker, occupants, datamanager, visitors and the like. Each of the plurality of users 128 isassociated with a task. For example, the human operators perform thetask of monitoring and regulating machines. In another example, thehuman workers perform the task of cleaning, sweeping and repairing. Inyet another example, the occupants are the employees that includemanagers, attendants, assistants, clerk, security staff and the like. Inyet another example, the occupants are visitors present for a specificperiod of time.

Each of the plurality of users 128 utilizes a pre-defined amount of theenergy. The pre-defined amount of the energy pertains to a correspondingenergy consuming device of the plurality of energy consuming devices104. Moreover, each of the plurality of energy consuming devices 104performs an operation to meet requirements of the plurality ofoperations associated with the built environment 102. The plurality ofoperations is associated with the operation of each of the plurality ofenergy consuming devices 104 installed in the built environment 102. Theplurality of energy consuming devices 104 may be of any type and size.In addition, the plurality of energy consuming devices 104 includes aplurality of electrical devices and a plurality of portablecommunication devices.

In an embodiment of the present disclosure, the plurality of energyconsuming devices 104 may have any electrical and mechanicalapplications. Examples of the plurality of energy consuming devices 104include but may not be limited to lighting circuits, refrigerationunits, air conditioning systems, information technology networks, gasboilers, hot water heater, escalators, and elevators. The plurality ofenergy consuming devices 104 consumes a pre-defined amount of the energybased on a power rating, duration of energy usage and the plurality ofoperations performed. The pre-defined amount of the energy consumed bythe plurality of energy consuming devices 104 is based on one or moreenergy physical variables. The one or more energy physical variablesinclude but may not be limited to a power factor, a phase angle, a powerfrequency, a voltage, a current load and a power demand.

The one or more energy physical variables of each of the plurality ofenergy consuming devices 104 is monitored and measured by a plurality ofenergy metering devices. Each of the plurality of energy consumingdevices 104 is combined with the plurality of energy metering devices.In an embodiment of the present disclosure, the plurality of energymetering devices is installed inside each of the plurality of energyconsuming devices 104. The plurality of energy metering devices measureseach of the one or more energy physical variables in real time. Theplurality of energy metering devices include but may not be limited todigital multi-meters, current sensors and wattage meters. In addition,the plurality of energy metering devices facilitates collection of afirst set of statistical data associated with the plurality of energyconsuming devices 104.

The collection of the first set of statistical data uses a method. In anembodiment of the present disclosure, the method involves digitalcollection of the first set of statistical data for each of theplurality of energy consuming devices 104. In another embodiment of thepresent disclosure, the method involves physical collection of the firstset of statistical data for each of the plurality of energy consumingdevices 104. The plurality of energy metering devices monitors a firstplurality of parameters. The first plurality of parameters is associatedwith the plurality of energy consuming devices 104. The first pluralityof parameters includes a set of operational characteristics and a set ofphysical characteristics. The set of operational characteristics includea current rating, a voltage rating, a power rating, a frequency ofoperation, an operating temperature and a device temperature. Inaddition, the set of operational characteristics include a duration ofthe energy usage by each of the plurality of energy consuming devices104 in the built environment 102. Moreover, the set of operationalcharacteristics include a seasonal variation in operation and anoff-seasonal variation in operation. Further, the set of physicalcharacteristics include a device size, a device area, a device physicallocation and a portability of device. In an embodiment of the presentdisclosure, the one or more energy metering devices collects the firstset of statistical data. In addition, the first set of statistical dataincludes a current operational state data and a past operational statedata. The current operational state data and the past operational statedata corresponds to current energy consumption data and the historicalenergy consumption data associated with the plurality of energyconsuming devices 104 of the built environment 102.

Going further, the plurality of energy consuming devices 104 isassociated with the plurality of users 128. The plurality of users 128interacts with the plurality of energy consuming devices 104 installedin the built environment 102 to perform specific operations. The dailyusage and the operating characteristics of the plurality of energyconsuming devices 104 are derived from an interface associated with eachuser of the plurality of users 128. Each of the plurality of energyconsuming devices 104 consumes a pre-defined amount of energy during theinterface. The pre-defined amount of energy is derived based on anenergy consumption behavior and an occupancy pattern of each of theplurality of users 128. In an example, each user of the plurality ofusers 128 in the built environment 102 may arrive and leave the builtenvironment 102 during certain hours each day.

Further, the energy consumption behavior and the occupancy pattern isrecorded for each of the plurality of users 128 to obtain a second setof statistical data. The energy consumption behavior and occupancypattern is collected and recorded by a plurality of occupancy detectionmeans. The plurality of occupancy detection means collect the energyconsumption behavior and occupancy pattern associated with the pluralityof users 128 in real time. The plurality of occupancy detection meansare installed inside and outside of the built environment 102. Theplurality of occupancy detection means include a plurality of occupancysensing devices. The plurality of occupancy sensing devices includeoccupancy sensors, door state sensors, motion detectors, microphones andradio frequency identification (hereinafter as “RFID”). In addition, theplurality of occupancy sensing devices include radio received signalstrength indicators (hereinafter as “RSSI”) and digital or radiofrequency signal processors. Furthermore, the plurality of occupancydetection means include the plurality of sensors 108. The plurality ofsensors 108 include carbon-monoxide sensors, carbon-dioxide sensors,heat sensors, pressure sensors, atmospheric pressure sensors,temperature sensors, energy flow sensors, energy fingerprint sensors onmonitored loads physical touch point sensors and the like.

The first set of statistical data and the second set of statistical datais transferred to the one or more data collecting devices 110 associatedwith the built environment 102. The one or more data collecting devices110 collects the first set of statistical data and the second set ofstatistical data. The one or more data collecting devices 110 performdigital collection and manual collection. In an embodiment of thepresent disclosure, each of the one or more data collecting devices 110is a portable device with an inbuilt API. The inbuilt API of each of theone or more data collection devices 110 is associated with a GlobalPositioning system (hereafter “GPS”). Further, the inbuilt API of eachof the one or more data collection devices 110 is associated with acamera and keypad designed for manual data input from the plurality ofusers 128. In another embodiment of the present disclosure, each of theone or more data collecting devices 110 is a cellular modem. In yetanother embodiment of the present disclosure, each of the one or moredata collecting devices 110 is any suitable data gateway device.

The one or more data collecting devices 110 collects a third set ofstatistical data associated with each of the plurality of energy storageand supply means 106. In an embodiment of the present disclosure, theone or more data collecting devices 110 receives the third set ofstatistical data from the plurality of energy monitoring devicesassociated with each of the plurality of energy storage and supply means106. The plurality of energy monitoring devices monitor a secondplurality of parameters associated with the plurality of energy storageand supply means 106. In addition, the plurality of energy monitoringdevices collect and transfer the second plurality of parametersassociated with the plurality of energy storage and supply means 106 tothe one or more data collecting devices 110 in real time. The secondplurality of parameters include but may not be limited to charging anddischarging rates, temperature characteristics, an energy storage andrelease capacity associated with the plurality of energy storage.

The one or more data collecting devices 110 is associated with thecommunication network 116 through an internet connection. The internetconnection is established based on a type of network. In an embodimentof the present disclosure, the type of network is a wireless mobilenetwork. In another embodiment of the present disclosure, the type ofnetwork is a wired network with a finite bandwidth. In yet anotherembodiment of the present disclosure, the type of network is acombination of the wireless and the wired network for the optimumthroughput of data transmission. The communication network 116 includesa set of channels with each channel of the set of channels supporting afinite bandwidth. The finite bandwidth of each channel of the set ofchannels is based on a capacity of the communication network 116. Thecommunication network 116 transmits a pre-defined size of the first setof statistical data, the second set of statistical data and the thirdset of statistical data to the energy demand control system 122. Thepre-defined size corresponding to the first set of statistical data, thesecond set of statistical data and the third set of statistical data ismeasured in terms of at least one of bits, bytes, kilobytes, megabytes,gigabytes, terabytes and petabytes. Accordingly, the energy demandcontrol system 122 receives the pre-defined size of the first set ofstatistical data, the second set of statistical data and the third setof statistical data. In addition, the energy demand control system 122receives another part of the first set of statistical data, the secondset of statistical data and the third set of statistical data from theplurality of external APIs 124 and third party databases.

Continuing with FIG. 1, the energy demand control system 122 receives afourth set of statistical data and a fifth set of statistical data. Theenergy demand control system 122 receives the fourth set of statisticaldata from the plurality of environmental sensors 118 through thecommunication network 116. The plurality of environmental sensors 118detect and collect environmental and weather conditions associated withthe built environment 102 in real time. In addition, the plurality ofenvironmental sensors 118 transfer the environmental and weatherconditions to the energy demand control system 122 in real time. In anembodiment of the present disclosure, the plurality of environmentalsensors 118 is present inside the built environment 102. In anotherembodiment of the present disclosure, the plurality of environmentalsensors 118 is present outside the built environment 102. Further, theenergy demand control system 122 receives the fifth set of statisticaldata from the plurality of energy pricing models 120. The plurality ofenergy pricing models 120 is configured to record energy pricesassociated with the built environment 102.

The energy demand control system 122 receives another part of the fourthset of statistical data and the fifth set of statistical data from theplurality of external APIs 124 and third party databases. The pluralityof external APIs 124 and the third party databases are configured tocollect, store and transmit weather history and weather forecasts. Inaddition, the plurality of external APIs 124 and the third partydatabases are configured to collect, store and transmit billing data, apast energy consumption data and metered energy data. Furthermore, theplurality of external APIs 124 and the third party databases areconfigured to collect, store and transmit financial or non-financialbusiness data. The financial or non-financial business data comes frombusiness management software. Example of the business managementsoftware includes Enterprise Resources Planning (ERP) software.

The energy demand control system 122 analyzes the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data. The analysis is done by performing one or morestatistical functions (discussed below in detailed description of FIG.2). The energy demand control system 122 performs the one or morestatistical functions to generate a plurality of statistical results.The plurality of statistical results pertains to the energy consumption(discussed below in detailed description of FIG. 2). The plurality ofstatistical results obtained from the analysis is used as a referencebasis of the energy consumption to execute the one or more controlroutines for controlling peak loading conditions. The one or morecontrol routines are executed by performing at least one of a pluralityof control techniques (as explained in the detailed description of FIG.2). In addition, the plurality of statistical results obtained from theanalysis is used to manipulate an optimized operating state of energyconsuming devices to efficiently reduce the time-variant energy demandand consumption of the built environment 102.

Further, the energy demand control system 122 displays each of theplurality of statistical results through an application installed in amobile phone, tablet, smart watch and the like. In another embodiment ofthe present disclosure, the energy demand control system 122 displayseach of the plurality of statistical results on a web page. In yetanother embodiment of the present disclosure, the energy demand controlsystem 122 displays each of the plurality of statistical results on aplurality of monitors. Furthermore, the energy demand control system 122manipulates the optimized operating state of each of the plurality ofenergy consuming devices. The energy demand control system 122 performsmanipulation to generate a peak level of energy demand concentrated overa limited period of time. Further, the energy demand control system 122integrates the plurality of energy storage and supply means forproviding an equivalent real time energy supply to selected energyconsuming devices (as discussed in detailed description of FIG. 2).

Further, the energy demand control system 122 transfers the plurality ofstatistical results along with the one or more control routines to theone or more statistical monitoring devices 126. The one or morestatistical monitoring devices 126 is configured to receive and displayat least one of the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data and the fifth set of statistical data. In addition, theone or more statistical monitoring devices 126 are configured to receiveand display at least one of the plurality of statistical results and theone or more control routines for proper monitoring and regulation. Theone or more statistical monitoring devices 126 is a device capable ofreceiving the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data and the fifth set of statistical data from the energydemand control system 122. Also, the one or more statistical monitoringdevices 126 is a device capable of receiving the plurality ofstatistical results and the one or more control routines from the energydemand control system 122.

It may be noted that in FIG. 1, the energy demand control system 122transfers the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data, the fifth set of statistical data, the plurality ofstatistical results and the one or more control routines to the one ormore statistical monitoring devices 126; however, those skilled in theart would appreciate that the energy demand control system 122 transfersthe first set of statistical data, the second set of statistical data,the third set of statistical data, the fourth set of statistical dataand the fifth set of statistical data, the plurality of statisticalresults and the one or more control routines to more number ofstatistical monitoring devices. Furthermore, it may be noted that inFIG. 1, the built environment 102 is connected to the energy demandcontrol system 122 through the communication network 116; however, thoseskilled in the art would appreciate that more number of builtenvironments are connected to the energy demand control system 122through the communication network 116.

FIG. 2 illustrates a block diagram 200 for manipulating the load curvescorresponding to the time-variant energy demand and consumption of thebuilt environment 102, in accordance with various embodiments of thepresent disclosure. It may be noted that to explain the system elementsof FIG. 2, references will be made to the system elements of the FIG. 1.

The block diagram 200 includes the built environment 102, commercialpower supply grid node 112, the one or more renewable energy supplysources 114, the energy demand control system 122 and the plurality ofexternal APIs 124 (as discussed above in detailed description of FIG.1). In addition, the block diagram 200 includes the plurality ofenvironmental sensors 118 and the plurality of energy pricing models 120and the one or more statistical monitoring devices 126 (as discussedabove in detailed description of FIG. 1). Moreover, the block diagram200 includes a network based automatic control system 202 and thirdparty databases 206. Furthermore, the energy demand control system 122includes a server 204. In addition, the server 204 includes a database204 a and a processor 204 b.

Each of the plurality of energy consuming devices 104 is associated withone or more energy physical variables (as described above in detaileddescription of FIG. 1). The one or more energy physical variablesdefines the energy consumption in the real time based on the load. In anembodiment of the present disclosure, each of the plurality of energyconsuming devices 104 is associated with the plurality of energymetering devices. The plurality of energy metering devices digitallymeasures one or more energy physical variables in the real time toobtain the first set of statistical data (as discussed above in detaileddescription of FIG. 1). The plurality of energy metering devicesincludes one or more digital meters, one or more digital current andvoltage sensors, the multi-meters, watt-meters, supervisory control anddata acquisition (SCADA) and the like.

The energy demand control system 122 collects the first set ofstatistical data associated with the plurality of energy consumingdevices 104 from the plurality of energy metering devices. The first setof statistical data includes a current operational state data associatedwith the plurality of energy consuming devices 104 and a pastoperational state data associated with the plurality of energy consumingdevices 104. The operational state data is associated with thepre-defined amount of energy consume by each of the plurality of energyconsuming devices 104 in real time. The plurality of energy consumingdevices 104 consume the pre-defined amount of energy to perform aspecific operation (as discussed above in detailed description of FIG.1).

Further, the energy demand control system 122 fetches the second set ofstatistical data associated with an occupancy behavior of the pluralityof users 128 present inside each of the built environment 102. Theenergy demand control system 122 fetches the second set of statisticaldata from the plurality of occupancy detection means. The second set ofstatistical data includes a first plurality of occupancy data and asecond plurality of occupancy data. The first plurality of occupancydata is associated with energy consumption behavior of each of theplurality of users 128 present inside the built environment 102. Thesecond plurality of occupancy data is associated with the occupancypattern of each of the plurality of users 128 present inside the builtenvironment 102.

The first plurality of occupancy data is associated with interactionbetween the plurality of energy consuming devices 104 and the pluralityof users 128. In an example, a person X check-in to a hotel A. Theperson X uses the elevator to go upstairs, unlock the room by digitalcard swap and turns on the lighting and air conditioning unit. Theinteraction of the person X with the elevator, the digital card swapsdoor, the lightings and the air conditioning unit results in thepre-defined load consumption. The plurality of users 128 consumes thepre-defined amount of energy associated with the built environment 102.The second plurality of occupancy data is associated with the occupancypattern of the plurality of users 128. The occupancy pattern of theplurality of users 128 varies with time, location, weather, season andthe like. The occupancy pattern of the plurality of users 128 varieswith different zones of the built environment 102. In an example, theoccupancy pattern of the plurality of users 128 in shopping mallsincreases during the festive seasons. In another example, the occupancypattern at the rugby ground increases during the match day.

The energy consumption behavior and occupancy pattern is recorded andcounted by the plurality of occupancy detection means to obtain thesecond set of statistical data (as described above in detaileddescription of FIG. 1). In addition, the plurality of occupancydetection means record and count based on the one or morespecifications. The one or more specifications include heat signature,identification cards, Bluetooth and the like. In an example, the recordof first time visitors and frequent visitors is maintained for fastercollection of the second set of statistical data. Further, the energyusage pattern of each of the plurality of users 128 creates a unique andaggregated consumption of the energy. The unique and aggregatedconsumption of the energy is based on a variation in number of theplurality of users 128. The variation in the number of the plurality ofusers 128 may be based on days, months, seasons, events and time ofyear. In addition, the variation in the number of the plurality of users128 may be based on architectural configurations of the builtenvironment 102. In an example, the occupancy pattern of the pluralityof users 128 in shopping malls increases during the festive seasons. Inanother example, the occupancy pattern at the soccer ground increasesduring the match day.

Further, the energy demand control system 122 accumulates the third setof statistical data associated with each of the plurality of energystorage and supply means 106 from the plurality of energy monitoringdevices. The third set of statistical data includes a current andhistorical energy storage and supply capacity data associated with theplurality of energy storage and supply means 106. The plurality ofenergy monitoring devices record and collect energy storage and supplycapacity data associated with the plurality of energy storage and supplymeans 106 to obtain the third set of statistical data. The energy demandcontrol system 122 accumulates the third set of statistical data basedon the second plurality of parameters (as mentioned above in detaileddescription of FIG. 1).

The energy demand control system 122 receives the fourth set ofstatistical data from the plurality of environmental sensors 118associated with the built environment 102 (discussed above in detaileddescription of FIG. 1). In addition, the energy demand control system122 receives the fourth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206. The fourth set ofstatistical data includes the current and historical environmentalcondition data of at least one of inside and outside of the builtenvironment 102. The fourth set of statistical data is received by theenergy demand control system 122 based on a third plurality ofparameters. In an embodiment of the present disclosure, the thirdplurality of parameters include but may not be limited to a means ofrecording environmental data having temperature, humidity and airpressure associated with each of the plurality of environmental sensors.

Further, the energy demand control system 122 gathers the fifth set ofstatistical data from the plurality of energy pricing models 120. Thefifth set of statistical data includes current and historical recordingsof energy pricing state affecting the built environment 102. Theplurality of energy pricing models 120 record and transfer the energypricing to the energy demand control system 122 in real time through thecommunication network 116. In addition, the energy demand control system122 gathers the fifth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206 (as discussed abovein detailed description of FIG. 1). The fifth set of statistical data isgathered based on a fourth plurality of parameters. In an embodiment ofthe present disclosure, the fourth plurality of parameters include ameans of recording energy pricing data having an energy pricing model,an energy price signal associated with the built environment 102.

Going further, the energy demand control system 122 performs theanalysis of the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data and the fifth set of statistical data. The energydemand control system 122 performs the one or more statistical functionsto generate the plurality of statistical results. The one or morestatistical functions include translating the current operational statedata and the past operational state data associated with the pluralityof energy consuming devices 104 into energy demand values. In addition,the one or more statistical functions include parsing the first set ofstatistical data, the second set of statistical data and the third setof statistical data. The energy demand control system 122 develops anenergy usage profile. The energy demand control system 122 develops theenergy usage profile of each of the plurality of energy consumingdevices 104, each of the plurality of energy storage and supply means106 and each of the plurality of users 128. In addition, the energydemand control system 122 develops the energy usage profile associatedwith each zone, groups of zones, such as each floor of a building andeach of the one or more built environments.

Further, the one or more statistical functions include auto-fulfillingone or more data entries in the first set of statistical data, thesecond set of statistical data and the third set of statistical data.The auto-fulfilling of the one or more data entries is performed tominimize errors in deriving the energy consumption and demand associatedwith the built environment 102 for a given time interval. Moreover, theenergy demand control system 122 auto-fulfils the one or more dataentries by using an application of at least one of the statisticalregression, interpolation and extrapolation.

The one or more statistical functions include comparing the currentoperational state data with the past operational state data. The energydemand control system 122 compares the current operational state datawith the past operational state data associated with the each of theplurality of energy consuming devices 104. The current operational statedata and the past operational state data are compared to determine thepotential for improvement in energy consumption of each of the pluralityof energy consuming devices 104. In addition, the energy demand controlsystem 122 compares a current energy storage capacity and a past energystorage capacity associated with each of the plurality of energy storageand supply means 106. The current energy storage capacity and the pastenergy storage capacity are compared to determine the potential forimprovement in charge/discharge cycles and energy storage capacity ofeach of the plurality of energy storage and supply means 106.

Accordingly, the analysis of the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical dataprovides the plurality of statistical results. The plurality ofstatistical results pertains to the energy consumption. In addition, theplurality of statistical results is based on a statistical data model.The statistical data model provides a complete insight into the energyconsumption trend. The plurality of statistical results includes one ormore graphs, one or more charts, one or more tables and one or morestatistical maps of energy consumption. The plurality of statisticalresults is obtained as a function of duration of the operations of theplurality of energy consuming devices and energy storage and supplycapacity of the plurality of energy storage and supply means. Inaddition, the plurality of statistical results is obtained as a functionof environmental conditions, and energy pricing affecting the builtenvironment 102.

In an example, the plurality of statistical results include a table andchart of monthly energy consumption of the built environment 102 and atable of a total monthly variable energy load. In another example, theplurality of statistical results includes a pie chart to show aseparation of the energy use in the built environment 102 and a table ofenergy consumption per month associated with air conditioning loads. Inyet another example, the plurality of statistical results includes astatistical chart depicting a kWh consumption based on load type, a bargraph of expected air conditioner savings and service costs. In yetanother example, the plurality of statistical results include a barchart of gross rental, service and licensing costs of at least one ofair conditioning units, air conditioning control means, statisticalsoftware and networks. In yet another example, the plurality ofstatistical results includes the statistical chart of total kWh consumedper room as a function of cold degree days.

The energy demand control system 122 executes the one or more controlroutines for controlling the peak loading conditions associated with thebuilt environment 102. The energy demand control system 122 executes theone or more control routines based on the plurality of statisticalresults corresponding to the energy demand and consumption of the builtenvironment 102. In an embodiment, the energy demand control system 122executes the one or more control routines through the network basedautomatic control system 202. The network based automatic control system202 is associated with the built environment 102. In addition, thenetwork based automatic control system 202 is associated with aplurality of electrical control relays. In addition, the network basedautomatic control system 202 is associated with a microprocessor basedswitches. The network based automatic control system 202 sends one ormore control signals based on the one or more control routines. Thenetwork based automatic control system 202 automatically applies the oneor more control routines to the built environment 102.

The network based automatic control system 202 controls the operation ofeach of the plurality of energy consuming devices 104. In addition, thenetwork based automatic control system 202 controls the plurality ofenergy consuming devices 104 based on the occupancy behavior of theplurality of users 128 and energy storage capacity of the plurality ofenergy storage and supply means 106. Moreover, the network basedautomatic control system 202 controls the plurality of energy consumingdevices 104 based on weather conditions and real time energy pricingassociated with the built environment 102. Furthermore, the networkbased automatic control system 202 controls the plurality of energystorage and supply means 106 based on the real time energy demand,weather conditions and forecasts, and real time energy pricingassociated with the built environment 102.

The energy demand control system 122 executes the one or more controlroutines by performing at least one of the plurality of controltechniques. The energy demand control system 122 performs the pluralityof control techniques for generating an optimized time-variant energydemand associated with the built environment 102. In addition, theenergy demand control system 122 performs the plurality if controltechniques for rendering one or more gradual load curves associated withthe built environment 102. The one or more gradual load curvescorresponds to the optimized time-variant energy demand and consumptionassociated with the built environment 102. The plurality of controltechniques include at least one of a waveform analysis based controltechnique, a key performance indicator based control technique, aprioritization based control technique and an efficiency based controltechnique.

The energy demand control system 122 performs at least one of theplurality of control techniques to control the peak loading conditionsassociated with the built environment 102. In addition, the energydemand control system 122 executes each technique of the plurality oftechniques in a pre-defined sequence to establish a pre-defined controllevel. In an embodiment of the present disclosure, the energy demandcontrol system 122 executes the waveform analysis based controltechnique to establish a first control level. The waveform analysisbased control technique is performed by analyzing operating state of theplurality of energy consuming devices 104. The operating state of theplurality of energy consuming devices is analyzed in real time forregulating the operating states of each of the plurality of energyconsuming devices 104 in time series. The operating states of each ofthe plurality of energy consuming devices 104 is regulated so that theminimum possible number of load states gets overlapped at the same givenmoment in time. In an example of a hotel building, multiple airconditioning compressors may be turning on and off to transfer energyand maintain a specific temperature inside the building environment.Multiplied by 100 times, these air conditioners may coincidentallyoscillate on and off at the same time. The plurality of energy meteringdevices regularly collects and transmits the operating state of the airconditioning compressor as a value, on or off or zero to one hundred tothe energy demand control system 122. The waveform and frequency ofusage of each compressor is recorded for a pre-defined period of time.At a specific moment of time, the highest demand unit is operating at afrequency of 6 cycles per hour (the “frequency”) or 3 minutes (the“amplitude”) each 7 minutes. Also, the lowest demand unit is operatingat a frequency of 3 cycles per hour or 3 minutes each 17 minutes at thatspecific moment of time. The energy demand control system 122 executesthe waveform analysis based control technique by shifting each of the100 air conditioning unit cycles forwards or backwards in time toachieve a minimum energy consumption at the specific moment of time. Theenergy demand control system 122 executes the waveform analysis basedcontrol technique in a closed loop to optimize the operating state ofeach of the plurality of energy consuming devices.

In an embodiment of the present disclosure, the energy demand controlsystem 122 executes the waveform analysis based control techniquefollowed by the key performance indicator based control technique toestablish a second control level. The energy demand control system 122identifies and assigns the key performance indicators to each of theplurality of energy consuming devices 104. The energy demand controlsystem 122 identifies and assigns the key performance indicators basedon the operating state of each of the plurality of energy consumingdevices 104 over a period of time. Further, the energy demand controlsystem 122 compares the key performance indicators of each of theplurality of energy consuming devices 104 and prioritize the controlinstructions. In an example, an energy consuming device X is operatingat a relatively high frequency and amplitude than an energy consumingdevice Y for a given set of loads. The energy demand control system 122assigns a relatively lower key performance indicator to the energyconsuming device X as compared to the energy consuming device Y.Further, the energy demand control system 122 prioritize the controlinstructions for the energy consuming device Y over the controlinstructions for the energy consuming device X. In another example, acertain air conditioning compressor unit installed in room X may need tooperate substantially more than others within an artificially cooledbuilding due to the orientation and heat load from the sun. The energydemand control system 122 analyzes the current operating state, identifyand compare the key performance indicator of the air conditioningcompressor unit of room X with other air conditioning units. The energydemand control system 122 prioritize the air conditioning compressorinstalled in the room X over other air conditioning compressor unitsinstalled in the building. Further, the energy demand control unit 122implement the waveform analysis control technique for other airconditioning units prior to the air conditioning compressor unit of roomX.

In an embodiment of the present disclosure, the energy demand controlsystem 122 executes the plurality of control techniques associated withthe second control level followed by the prioritization based controltechnique to establish a third level control. The third control level isestablished by considering the second set of statistical data associatedwith the plurality of users 128 and the fourth set of statistical dataassociated with the environmental conditions. The second set ofstatistical data and the fourth set of statistical data are received bythe energy demand control system 122. The energy demand control system122 analyze the second set of statistical data and the fourth set ofstatistical data to generate a new set of key performance indicatorswith priority over a basic set associated with the second control level.The new set of key performance indicators are generated based ontemperature, occupancy associated with the built environment andhistorical performance and efficiencies of each of the plurality ofenergy consuming devices. Further, the energy demand control system 122prioritize one or more instructional control strategies based on theenvironmental conditions and occupancy. Moreover, the energy demandcontrol system prioritize the instructional control strategies for eachzone of the built environment 102. For example, in a hotel with manyrooms and many air conditioning compressors, the energy demand controlsystem 122 receives both the current operating state of the compressorfor each room as well as the current temperature and occupancy. Theenergy demand control system 122 prioritize the control strategies foreach room first by waveform characteristics (frequency and amplitude),then by current temperature for each room and finally by occupancy. Theenergy demand control system 122 provides a high level of manipulationpriority to the rooms with unoccupied state. The energy demand controlsystem 122 prioritize the instructional control strategies for theunoccupied rooms such that the frequency and amplitude of thoseunoccupied rooms gets lowered.

In an embodiment of the present disclosure, the energy demand controlsystem 122 executes the plurality of control techniques associated withthe third control level followed by the efficiency based controltechnique to establish a fourth control level. The energy demand controlsystem 122 improves an actual operating efficiency by regulating theoperating states of each of the plurality of energy consuming devices104 in real time. The energy demand control system 122 prioritize theinstructional control strategies to decrease the frequency of usage andincrease the amplitude of the plurality of energy consuming devices 104.In an example, the energy demand control system 122 establish the thirdcontrol level to optimize the operating state of the compressor with a 6cycles per hour frequency and a 3 minutes amplitude. Further, the energydemand control system 122 regulates the operating state of compressorwith the 6 cycles per hour frequency and the 3 minutes amplitude to 3cycles per hour frequency and a 6 minutes amplitude. This increases theefficiency of the compressor units by reducing the number of cyclesassociated with each compressor units. In addition, an average energyconsumption of 200 Watts per compressor per hour corresponding to the 6cycles per hour frequency and 3 minutes amplitude is reduced to 180Watts per compressor per hour corresponding to the 3 cycles per hourfrequency and 6 minutes amplitude. The energy demand control system 122continues to incrementally decrease the number of cycles to achieve theoptimum energy consumption. For example, if the cycle frequency wasfurther reduced to two, 9 minute cycles and the energy consumptionincreases from 180 Watts per compressor per hour to 190 Watts per hour,the energy demand control system 122 reverts the frequency or amplitudeback to optimal value of three, 6 minutes cycles.

Continuing with FIG. 2, the one or more control routines are executedfor optimizing the time variant energy demand and consumption associatedwith the built environment 102. In addition, the one or more controlroutines are executed for rendering the one or more gradual load curvesassociated with the built environment 102. In an embodiment of thepresent disclosure, the one or more gradual load curves are rendered inat least one of a gradually increasing shape, gradually decreasing shapeand flat shape. The one or more gradual load curves corresponds to theoptimized time-variant energy demand and consumption associated with thebuilt environment 102. The optimized time-variant energy demand andconsumption of the built environment 102 is further minimized bymanipulating the optimized operating state of each of the plurality ofenergy consuming devices 104.

The energy demand control system 122 manipulates the optimized operatingstate of each of the plurality of energy consuming devices 104. Theenergy demand control system 122 manipulates the optimized operatingstate by time-variant shifting of energy usage of each selected energyconsuming device of the plurality of energy consuming devices 104. Thetime-variant shifting of the energy usage is performed in a scheduledenergy usage profile of the selected energy consuming device of theplurality of energy consuming devices 104. The energy demand controlsystem 122 performs the time-variant shifting and scheduling to generatea peak level of energy demand concentrated over a limited period oftime. In an embodiment of the present disclosure, the time-variantshifting of energy usage is performed by shifting the operating cycle ofthe selected energy consuming devices of the plurality of energyconsuming devices 104 to at least one of forward and backward in realtime. In addition, the energy demand control system 122 performs thetime-variant shifting and scheduling to render one or more steep loadcurves associated with the built environment 102. The one or more steepload curves corresponds to the peak level of energy demand concentratedover a limited period of time.

Further, the energy demand control system 122 integrates the pluralityof energy storage and supply means 106 to the built environment 102. Theenergy demand control system 122 integrates the plurality of energystorage and supply means for optimally reducing the peak level of energydemand concentrated over the limited period of time. The energy demandcontrol system 122 monitors the manipulated operating state of each ofthe plurality of energy consuming devices 104, environmental conditionsassociated with the built environment and comfort level of each user ofthe plurality if users 128. In addition, the energy demand controlsystem 122 derives a threshold level associated with the comfort levelof the plurality of users, environmental conditions and energyconsumption of the built environment 102. The energy demand controlsystem 122 performs integration of the plurality of energy storage andsupply means based on validation of an increase in the energy demandabove the threshold level.

The energy demand control system 122 integrates the plurality of energystorage and supply means for providing the equivalent real time energysupply to the selected energy consuming devices from the plurality ofenergy storage and supply means. In addition, the integration isperformed for optimally reducing the peak level of energy demand of thebuilt environment 102 concentrated over the limited period of time. Theoptimal reduction of the peak level of energy demand provides at leastone of a first potential for optimum charge and a second potential ofoptimum discharge of the plurality of energy storage and supply meansover a period of time. The first potential for optimum charge and thesecond potential for optimum discharge results in a more effectivedemand reduction from the plurality of energy storage and supply meanshaving low energy storage capacity.

The integration of the plurality of energy storage and supply meanshaving low energy storage capacity includes a deeper potential forcharge and discharge over a shorter period of time. In an example of ahotel, 100 air conditioning units are operating in a pre-definedoperating cycles to maintain a consistent average indoor temperaturerange in accordance with the comfort design and demand of the guests.The energy demand control system 122 optimizes the energy demand byapplication of the first control level, the second control level, thethird control level and the fourth control level. The energy demandcontrol system 122 executes the one or more control routines to optimizethe maximum concurrent demand from 100 air conditioning unit to 20 airconditioning units. The maximum concurrent demand is reduced whilemaintaining the consistent average indoor temperature range inaccordance with the comfort design and demand of the buildingsoccupants. The energy demand control system 122 instructs all 20 airconditioning unit operating simultaneously to turn off resulting in arapid rise in temperature inside the hotel. This renders a steep andhollow energy demand curve associated with the energy usage profile ofthe hotel. The energy demand control system 122 monitors a real timetemperature rise within the hotel building and compares with thethreshold level. The energy demand control system 122 prompts the 40 airconditioning units to turn on resulting in faster recovery to a previousindoor temperature range. Further, the energy demand control system 122integrates the plurality of energy storage and supply means 106 todischarge and supply the equivalent real time energy to the additional20 air conditioning units. The additional 20 air conditioning unitsutilizes the energy discharged from the plurality of energy storage andsupply means 106. The energy consumption identical to the condition ofonly 20 air conditioning units operating for a given time interval ismaintained. This would provide an effective energy demand reductionprovided by the plurality of energy storage and supply means 106equivalent to the demand generated by 20 air conditioning units. Theenergy demand control system 122 prompts the plurality of energy storageand supply means 106 to stop supplying the equivalent real time energyas soon as average temperature requirement is restored in the builtenvironment 102. This results in a steep and short discharge intervalsof the plurality of energy storage and supply means 106.

In another example, 20 air conditioning units is controlled for a givenspecific indoor temperature requirement, based on given outdoor weatherconditions. The energy demand control system 122 alternate the operationof 10 air conditioning units in sequence with the charge and dischargecycles of the plurality of energy storage and supply means 106. Thisreduces the sinusoidal net average demand, while maintaining the averageindoor temperature. The energy demand control system 122 prompts the 10air conditioning units to turn off, leaving 10 air conditioning unitsoperating at a specific time interval. In addition, the energy demandcontrol system 122 prompts the plurality of energy storage and supplymeans 106 to start charging at a rate equivalent to the powerconsumption of 10 AC units such that the total net demand remainsequivalent to 20 air conditioning units. This results in a steep andshort charge intervals of the plurality of energy storage and supplymeans 106.

The energy demand control system 122 stores the first set of statisticaldata, the second set of statistical data, the third set of statisticaldata, the fourth set of statistical data and the fifth set ofstatistical data in the database 204 a in real time. In addition, theenergy demand control system 122 stores the plurality of statisticalresults and the key performance indicators in the database 204 a in realtime. Moreover, the energy demand control system 122 stores a log filehaving the one or more control routines in the database 204 a in realtime.

The energy demand control system 122 updates the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data in real time. In addition, the energy demand controlsystem 122 updates the plurality of statistical results and the keyperformance indicators in real time. Moreover, the energy demand controlsystem 122 updates the log file having the one or more control routinesin real time.

The energy demand control system 122 displays at least one of the firstset of statistical data, the second set of statistical data, the thirdset of statistical data, the fourth set of statistical data and thefifth set of statistical data on the one or more statistical monitoringdevices 126. In addition, the energy demand control system 122 displaysat least one of the plurality of statistical results and the keyperformance indicators on the one or more statistical monitoring devices126 in real time. Moreover, the energy demand control system 122displays the log file having the one or more control routines in realtime.

FIG. 3 illustrates a block diagram 300 of the energy demand controlsystem 122, in accordance with various embodiment of the presentdisclosure. It may be noted that to explain the system elements of FIG.3, references will be made to the system elements of the FIG. 1 and theFIG. 2. The energy demand control system 122 includes a collectionmodule 302, a fetching module 304, an accumulation module 306, areception module 308, a gathering module 310 and an analyzing module312. In addition, the energy demand control system 122 includes anexecution module 314, a manipulation module 316 and an integrationmodule 318. Moreover, the energy demand control system 122 includes astorage module 320, an updating module 322 and a displaying module 324.The above mentioned modules are configured for manipulating the loadcurves corresponding to the time-variant energy demand and consumptionof the built environment 102 associated with the one or more renewableenergy supply sources.

The collection module 302 collects the first set of statistical dataassociated with each of the plurality of energy consuming devices 104installed in the built environment 102. The first set of statisticaldata includes the current operational state data and the pastoperational state data associated with the plurality of energy consumingdevices 104. The plurality of energy metering devices collects the firstset of statistical data. The plurality of energy metering devicestransfer the first set of statistical data to the one or more datacollecting devices 110. The one or more data collecting devices 110transfer the first set of statistical data to the energy demand controlsystem 122 (as explained above in the detailed description of FIG. 1 andFIG. 2).

The fetching module 304 fetches the second set of statistical dataassociated with the occupancy behavior of the plurality of users 128present inside the built environment 102. The second set of statisticaldata includes the energy consumption behavior of each of the pluralityof users 128 present inside the built environment 102. In addition, thesecond set of statistical data includes the occupancy pattern of each ofthe plurality of users 128 present inside the built environment 102. Theplurality of occupancy detection means and the plurality of sensors 108fetches the second set of statistical data in real time. In addition,the plurality of occupancy detection means and the plurality of sensors108 transfer the second set of statistical data to the energy demandcontrol system 122 (as discussed above in detailed description of FIG. 1and FIG. 2).

The accumulation module 306 accumulates the third set of statisticaldata associated with each of the plurality of energy storage and supplymeans 106 associated with the built environment 102. The third set ofstatistical data includes the current and historical energy storage andsupply capacity data associated with the plurality of energy storage andsupply means 106. The plurality of energy monitoring devices accumulatesthe energy storage and supply capacity data associated with each of theplurality of energy storage and supply means 106 in real time to obtainthe third set of statistical data. In addition, the plurality of energymonitoring devices transfer the third set of statistical data to theenergy demand control system 122 (as explained above in detaileddescription of FIG. 1 and FIG. 2).

The reception module 308 receives the fourth set of statistical dataassociated with each of the plurality of environmental sensors 118. Thefourth set of statistical data includes the current and historicalenvironmental condition data of at least one of inside and outside ofthe built environment 102. The plurality of environmental sensors 118records the environmental condition data in real time to obtain thefourth set of statistical data. In addition, the plurality ofenvironmental sensors 118 transfers the fourth set of statistical datato the energy demand control system 122. Moreover, the reception module308 receives the fourth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206 (as discussed abovein detailed description of FIG. 1 and FIG. 2).

The gathering module 310 gathers the fifth set of statistical dataassociated with each of the plurality of energy pricing models 120. Thefifth set of statistical data includes the current and historicalrecordings of the energy pricing state affecting the built environment102. The plurality of energy pricing models 120 record the real timeenergy pricing state associated with the built environment 102 to obtainthe fifth set of statistical data. In addition, the plurality of energypricing models transfer the fifth set of statistical data to the energydemand control system 122. Moreover, the gathering module 310 gathersthe fifth set of statistical data from the plurality of external APIs124 and the third party databases 206 (as explained above in detaileddescription of FIG. 1 and FIG. 2).

The analyzing module 312 analyzes the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data.The analyzing module 312 includes a translation module 312 a, a parsingmodule 312 b, an auto-fulfilling module 312 c and a comparison module312 d. The translation module 312 a translates the current operationalstate data and the past operational state data associated with theplurality of energy consuming devices 104 into the energy demand values.In addition, the translation module 312 a translates the currentoperational state data and the past operational state data into theenergy demand values for the pre-defined interval of time. The parsingmodule 312 b parses the first set of statistical data, the second set ofstatistical data and the third set of statistical data. The parsingmodule 312 b parses the first set of statistical data, the second set ofstatistical data and the third set of statistical data based on thephysical location of each of the plurality of energy consuming devices104. In addition, the parsing module 312 b parses the first set ofstatistical data, the second set of statistical data and the third setof statistical data based on the occupancy pattern of the plurality ofusers 128. Moreover, the parsing module 213 b parses the first set ofstatistical data, the second set of statistical data and the third setof statistical data based on the weather conditions and real time energypricing state. The auto-fulfilling module 312 c auto-fulfils the one ormore data entries in the first set of statistical data, the second setof statistical data and the third set of statistical data. Furthermore,the comparison module 312 d compares the current operational state datawith the past operational state data associated with the each of theplurality of energy consuming devices 104. In addition, the comparisonmodule 312 d compares the current energy storage capacity and the pastenergy storage capacity associated with each of the plurality of energystorage and supply means 106 (as discussed above in detailed descriptionof FIG. 2).

The analysis is performed to generate the plurality of statisticalresults associated with the energy consumption of the built environment102 in real time. The plurality of statistical results includes one ormore graphs, one or more charts, one or more tables and one or morestatistical maps of the energy consumption as a function of duration ofthe operations. Further, the plurality of statistical results includesbase-load, variable load, the cost of the operations, energy efficiency,the temperature, humidity and daylight. Furthermore, the plurality ofstatistical results includes the real time occupancy of the plurality ofusers 128 inside the built environment 102 and physical parameters ofeach of the plurality of energy consuming devices.

The execution module 314 executes the one or more control routines forcontrolling peak loading conditions associated with the builtenvironment 102. The execution module 314 perform execution on theplurality of statistical results. The one or more control routines beingexecuted by performing at least one of the plurality of controltechniques. The execution module 314 performs the plurality of controltechniques for generating the optimized time variant energy demand andconsumption and rendering the one or more gradual load curves associatedwith the built environment 102. Moreover, the execution module 314executes the one or more control routines through the network basedautomatic control system 202. The network based automatic control system202 automatically applies the one or more control routines to the builtenvironment 102 (as discussed in detailed description of FIG. 2).

The manipulation module 316 manipulates the optimized operating state ofeach of the plurality of energy consuming devices 104. The manipulationmodule 316 manipulates the optimized operating state by time-variantshifting of energy usage of each selected energy consuming device of theplurality of energy consuming devices 104. The time-variant shifting ofthe energy usage is performed in the scheduled energy usage profile ofthe selected energy consuming device of the plurality of energyconsuming devices 104. The manipulation module 316 performs thetime-variant shifting and scheduling to generate the peak level ofenergy demand concentrated over the limited period of time. Moreover,the manipulation module 316 manipulates the optimized operating state torender the one or more steep load curves associated with the peak levelof energy demand of the built environment 102 (as explained in thedetailed description of FIG. 2).

The integration module 318 integrates the plurality of energy storageand supply means for providing an equivalent real time energy supply tothe selected energy consuming devices of the plurality of energyconsuming devices 104. The integration module 318 integrates theplurality of energy storage and supply means based on validation of theincrease in the energy demand above the threshold level. The integrationmodule 318 performs integration for optimally reducing the peak level ofenergy demand concentrated over the limited period of time (as explainedin the detailed description of FIG. 2).

The storage module 320 stores the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data inthe database 204 a in real time. In addition, the storage module 320stores the plurality of statistical results and the key performanceindicators in the database 204 a in real time. Moreover, the storing 320stores the log file having the one or more control routines in thedatabase 204 a in real time. The database 204 a is associated with theserver 204 of the energy demand control system 122.

The updating module 322 updates the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data inreal time. In addition, the updating module 322 updates the plurality ofstatistical results and the key performance indicators in real time.Moreover, the updating module 322 updates the log file having the one ormore control routines in real time.

The displaying module 324 displays the first set of statistical data,the second set of statistical data, the third set of statistical data,the fourth set of statistical data and the fifth set of statistical dataon the one or more statistical monitoring devices 126. In addition, thedisplaying module 324 displays the plurality of statistical results andthe key performance indicators on the one or more statistical monitoringdevices 126 in real time. Moreover, the displaying module 324 displaysthe log file having the one or more control routines in real time.

FIG. 4 illustrates a flow chart 400 for manipulating the load curvescorresponding to the time-variant energy demand and consumption of thebuilt environment, in accordance with various embodiments of the presentdisclosure. It may be noted that to explain the process steps offlowchart 400, references will be made to the system elements of FIG. 1,FIG. 2 and FIG. 3. It may also be noted that the flowchart 400 may havelesser or more number of steps.

The flowchart 400 initiates at step 402. Following step 402, at step404, the analyzing module 312 analyzes the first set of statisticaldata, the second set of statistical data, the third set of statisticaldata, the fourth set of statistical data and the fifth set ofstatistical data by performing the one or more statistical functions.The analyzing module 312 analyze to obtain the plurality of statisticalresults. Further at step 406, the execution module 314 executes the oneor more control routines. The one or more control routines are executedfor generating the optimized time variant energy demand and consumptionand rendering the one or more gradual load curves associated with thebuilt environment 102. Further, at step 408, the manipulation module 316manipulates the optimized operating state of each of the plurality ofenergy consuming devices 104. The manipulation module 316 manipulates togenerate the peak level of energy demand concentrated over the limitedperiod of time and rendering the one or more steep load curvesassociated with the built environment 102. At step 410, the integrationmodule 318 integrates the plurality of energy storage and supply means106. The plurality of energy storage and supply means 106 is integratedfor providing the equivalent real time energy supply to the selectedenergy consuming devices. The flow chart 400 terminates at step 412.

FIG. 5 illustrates a block diagram of a computing device 500, inaccordance with various embodiments of the present disclosure. Thecomputing device 500 includes a bus 502 that directly or indirectlycouples the following devices: memory 504, one or more processors 506,one or more presentation components 508, one or more input/output (I/O)ports 510, one or more input/output components 512, and an illustrativepower supply 514. The bus 502 represents what may be one or more busses(such as an address bus, data bus, or combination thereof). Although thevarious blocks of FIG. 5 are shown with lines for the sake of clarity,in reality, delineating various components is not so clear, andmetaphorically, the lines would more accurately be grey and fuzzy. Forexample, one may consider a presentation component such as a displaydevice to be an I/O component. Also, processors have memory. Theinventors recognize that such is the nature of the art, and reiteratethat the diagram of FIG. 5 is merely illustrative of an exemplarycomputing device 500 that can be used in connection with one or moreembodiments of the present invention. Distinction is not made betweensuch categories as “workstation,” “server,” “laptop,” “hand-helddevice,” etc., as all are contemplated within the scope of FIG. 5 andreference to “computing device.” The computing device 500 typicallyincludes a variety of computer-readable media. The computer-readablemedia can be any available media that can be accessed by the computingdevice 500 and includes both volatile and nonvolatile media, removableand non-removable media. By way of example, and not limitation, thecomputer-readable media may comprise computer storage media andcommunication media. The computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer-readableinstructions, data structures, program modules or other data. Thecomputer storage media includes, but is not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium which can be used to store the desired informationand which can be accessed by the computing device 500. The communicationmedia typically embodies computer-readable instructions, datastructures, program modules or other data in a modulated data signalsuch as a carrier wave or other transport mechanism and includes anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared and other wireless media. Combinations of any ofthe above should also be included within the scope of computer-readablemedia.

Memory 504 includes computer-storage media in the form of volatileand/or nonvolatile memory. The memory 504 may be removable,non-removable, or a combination thereof. Exemplary hardware devicesinclude solid-state memory, hard drives, optical-disc drives, etc. Thecomputing device 500 includes one or more processors that read data fromvarious entities such as memory 504 or I/O components 512. The one ormore presentation components 508 present data indications to a user orother device. Exemplary presentation components include a displaydevice, speaker, printing component, vibrating component, etc. The oneor more I/O ports 510 allow the computing device 500 to be logicallycoupled to other devices including the one or more I/O components 512,some of which may be built in. Illustrative components include amicrophone, joystick, game pad, satellite dish, scanner, printer,wireless device, etc.

The present disclosure has many advantages over the existing art. Thepresent disclosure provides technical advantages, economic advantages aswell as ancillary benefits. The present disclosure enables theutilization of the energy storage and supply means having relativelysmaller size and energy storage capacity for addressing the sametime-variant load reduction requirements. In addition, the presentdisclosure controls a large amount of energy loads or demands and costassociated with the installation and operations. Moreover, the presentdisclosure provides a stable grid network resulting in stable energypricing and removing volatility of current power system designs.

The foregoing descriptions of specific embodiments of the presenttechnology have been presented for purposes of illustration anddescription. They are not intended to be exhaustive or to limit thepresent technology to the precise forms disclosed, and obviously manymodifications and variations are possible in light of the aboveteaching. The embodiments were chosen and described in order to bestexplain the principles of the present technology and its practicalapplication, to thereby enable others skilled in the art to best utilizethe present technology and various embodiments with variousmodifications as are suited to the particular use contemplated. It isunderstood that various omissions and substitutions of equivalents arecontemplated as circumstance may suggest or render expedient, but suchare intended to cover the application or implementation withoutdeparting from the spirit or scope of the claims of the presenttechnology.

While several possible embodiments of the invention have been describedabove and illustrated in some cases, it should be interpreted andunderstood as to have been presented only by way of illustration andexample, but not by limitation. Thus, the breadth and scope of apreferred embodiment should not be limited by any of the above-describedexemplary embodiments.

What is claimed is:
 1. A method for managing renewable energy sources,the method comprising: analyzing, at an energy demand control system, afirst set of statistical data associated with a plurality of energyconsuming devices, a second set of statistical data associated with anoccupancy behavior of a plurality of users, a third set of statisticaldata associated with a plurality of energy storage and supply systems, afourth set of statistical data associated with a plurality ofenvironmental sensors and a fifth set of statistical data associatedwith a plurality of energy pricing models, by performing one or morestatistical functions to generate a plurality of statistical results;executing, at the energy demand control system, one or more controlroutines for controlling peak loading conditions for the renewableenergy sources, wherein the control routines are based on the pluralityof statistical results, wherein the one or more control routines beingexecuted by performing at least one of a plurality of control techniquesand wherein the plurality of control techniques being performed forgenerating an optimized time variant energy demand and consumption andrendering one or more gradual load curves associated with a builtenvironment; manipulating, at the energy demand control system, anoptimized operating state of each of the plurality of energy consumingdevices using time-variant shifting of energy usage of each of theplurality of energy consuming devices in a scheduled energy usageprofile associated with each of the plurality of energy consumingdevices, wherein the time-variant shifting and scheduling beingperformed for generating a peak level of energy demand concentrated overa limited period of time and rendering one or more steep load curves;integrating, at the energy demand control system, the plurality ofenergy storage and supply systems for providing an equivalent real timeenergy supply to selected energy consuming devices of the plurality ofenergy consuming devices, based on validation of an increase in theenergy demand above a threshold level.
 2. The method of claim 1, whereinthe integration being performed for optimally reducing the peak level ofenergy demand concentrated over the limited period of time and whereinthe optimal reduction of the peak level of energy demand provides atleast one of a first potential for optimum charge and a second potentialof optimum discharge of the plurality of energy storage and supply meansover a period of time.
 3. The method of claim 1, wherein the pluralityof control techniques comprises a waveform analysis based controltechnique, a key performance indicator based control technique, aprioritization based control technique and an efficiency based controltechnique.
 4. The method of claim 1, wherein the analyzing, theexecuting, the manipulating and the integrating are performed in acontinuous closed loop with feedback loop for optimizing thetime-variant energy demand and consumption.
 5. The method of claim 1,wherein the plurality of energy storage and supply means comprises atleast one of a battery storage, a flywheel energy storage, a pumpedliquid system, and a system capable of storing, transferring andreleasing thermal energy.
 6. The method of claim 1, further comprisingcollecting, at the energy demand control system, the first set ofstatistical data, wherein the first set of statistical data comprises acurrent operational state data and a past operational state dataassociated with each of the plurality of energy consuming devices, basedon a first plurality of parameters, wherein the first plurality ofparameters comprises a set of operational characteristics and a set ofphysical characteristics associated with each of the plurality of energyconsuming devices comprising a current rating, a voltage rating, a powerrating, a frequency of operation, an operating temperature, a devicetemperature, the duration of operation, a seasonal variation inoperation and off-seasonal variation in operation and wherein the set ofphysical characteristics comprises a device size, a device area, adevice physical location and a portability of device and wherein thefirst set of statistical data being collected in real time.
 7. Themethod of claim 1, further comprising fetching, at the energy demandcontrol system, the second set of statistical data associated with theoccupancy behavior of the plurality of users, wherein the second set ofstatistical data comprises a first plurality of occupancy data and asecond plurality of occupancy data, wherein the first plurality ofoccupancy data being associated with energy consumption behavior of eachuser of the plurality of users and the second plurality of occupancydata being associated with an occupancy pattern of each user of theplurality of users.
 8. The method of claim 1, further comprisingaccumulating, at the energy demand control system, the third set ofstatistical data associated with each of the plurality of energy storageand supply systems, wherein the third set of statistical data comprisesa current and historical energy storage and supply capacity dataassociated with each of the plurality of energy storage and supplysystems, wherein the accumulation of the third set of statistical datais performed based on a second plurality of parameters, wherein thesecond plurality of parameters comprises at least one of charging anddischarging rates, temperature characteristics, an energy storage andrelease capacity, and wherein the third set of statistical data beingaccumulated in real time.
 9. The method of claim 1, further comprisingreceiving, at the energy demand control system, the fourth set ofstatistical data associated with each of the plurality of environmentalsensors, wherein the fourth set of statistical data comprises a currentand historical environmental condition data of at least inside andoutside the one or more built environments, wherein the reception of thefourth set of statistical data is performed based on a third pluralityof parameters, wherein the third plurality of parameters comprisestemperature, humidity and air pressure associated with each of theplurality of environmental sensors, and wherein the environmental databeing obtained from a plurality of external application programminginterfaces and a plurality of third party databases and wherein thefourth set of statistical data being received in real time.
 10. Themethod of claim 1, further comprising gathering, at the energy demandcontrol system, the fifth set of statistical data associated with eachof the plurality of energy pricing models, wherein the fifth set ofstatistical data comprises current and historical recordings of energypricing state affecting the one or more built environments, based on afourth plurality of parameters, wherein the fourth plurality ofparameters comprises energy pricing data including an energy pricingmodel or an energy price signal, and wherein the energy pricing databeing obtained from a plurality of external application programminginterfaces and a plurality of third party databases and wherein thefifth set of statistical data being gathered in real time.
 11. Themethod of claim 1, wherein the one or more statistical functionscomprises: translating current operational state data and pastoperational state data associated with the plurality of energy consumingdevices into energy demand values for a pre-defined interval of time;parsing the first set of statistical data, the second set of statisticaldata and the third set of statistical data; auto-fulfilling one or moredata entries in the first set of statistical data, the second set ofstatistical data and the third set of statistical data based on aself-learning algorithm; and comparing the current operational statedata with the past operational state data to determine potential forimprovement in energy consumption of each of the plurality of energyconsuming devices.
 12. The method of claim 1, wherein the plurality ofstatistical results comprises one or more graphs, one or more charts,one or more tables and one or more statistical maps of energyconsumption as a function of duration of the operations of the pluralityof energy consuming devices, energy storage and supply capacity of theplurality of energy storage and supply systems, environmental conditionsand energy pricing.
 13. The method of claim 1, further comprisingstoring, at the energy demand control system, the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data, the fifth set ofstatistical data, the plurality of statistical results, key performanceindicators and a log file having the one or more control routines in adatabase.
 14. The method of claim 1, further comprising updating, at theenergy demand control system, the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data, the fifth set of statistical data, theplurality of statistical results, key performance indicators and a logfile having the one or more control routines.
 15. The method of claim 1,further comprising displaying, at the energy demand control system, thefirst set of statistical data, the second set of statistical data, thethird set of statistical data, the fourth set of statistical data, thefifth set of statistical data, the plurality of statistical result, keyperformance indicators and a log file having the one or more controlroutines, wherein the displaying being provided on one or morestatistical monitoring devices in real time.